One health enteric package v1.0: Expanded and standardized metadata for enteric genomic epidemiology in the U.S

Authors: BALKEY, MARIA - Us Food & Drug Administration (FDA); TIMME, RUTH - Us Food & Drug Administration (FDA); GRIM, CHRISTOPHER - Us Food & Drug Administration (FDA); BATZ, MICHAEL - Us Food & Drug Administration (FDA); HICKS, JESSICA - Animal And Plant Health Inspection Service (APHIS); COOK, KIMBERLY - US Department Of Agriculture (USDA); Van Kessel, Jo Ann; BONO, JIM - US Department Of Agriculture (USDA); HARRIS, BETH - Animal And Plant Health Inspection Service (APHIS); KATZ, LEE - Centers For Disease Control And Prevention (CDC) - United States; ADAMS, JENNIFER - Centers For Disease Control And Prevention (CDC) - United States; STROIKA, STEVEN - Collaborator; JOSEPH, LAVIN - Centers For Disease Control And Prevention (CDC) - United States; FELDGARDEN, MIKE - Centers For Disease Control And Prevention (CDC) - United States

Submitted to: Food Production and Consumption International Workshop Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 5/26/2021
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Background: Databases of genomic data from foodborne pathogens found in human and non-human sources (food, food facilities, animals, and other environmental sources) represent a highly valuable resource for outbreak investigation and foodborne pathogen surveillance. The integration of genomics and epidemiological data contributes to a better understanding of foodborne pathogen outbreaks and where the pathogens reside in the environment, water, or wildlife, on farms or in food production facilities. An effective surveillance system contains genomics records and their corresponding contextual metadata that describe the different aspects of the genomics from foodborne pathogens in terms of isolate/sample attributes such as: “organism name”, “collected by”, “isolation source”, “collection date” and “geographic location”. These fields are currently described using standard terminologies at the level of “collection date”, controlled vocabularies for “geographic location” and taxonomies for organism name while “isolation source” and “collected by” fields are described as free text. This type of metadata supports cluster detection, outbreak investigation and pathogen surveillance, but more sophisticated and large-scale analysis to assess risk, root cause or source attribution requires standard, structured and highly granular metadata. To improve the metadata associated with genomic records from foodborne pathogens, we propose an expanded and standardized metadata package to be used for all US contributors across our open genomic epidemiology network for enteric surveillance. Ontology: The full potential of genomic data associated with foodborne pathogens requires metadata using standard terminologies that adhere to FAIR (Findable, Accessible, Interoperable and Reusable) principles. The complexity of the food supply can be described as the interaction of a wide range of products, processes, and environments. FoodON, the “farm to fork ontology,” comprehensively represents the food domain, becoming an essential tool to annotate and represent metadata for genomics from foodborne pathogens. Additionally, FoodON provides working terminology and relationships, from ontologies in the environmental, biological, anatomical, and chemical domains that are essential to capture the diverse sources of foodborne pathogens. Methods: The Interagency Collaboration on Genomics and Food Safety (Gen-FS) metadata working group, composed of USDA-FSIS, USDA-ARS, USDA-APHIS, FDA, CDC, and NCBI, reviewed the existing NCBI standard pathogen metadata package and used the recently described Food Environmental Metadata Standard for metagenomics data to develop the One Health Enteric Package v1.0. Attributes to describe isolate and sample metadata are grouped in six sections within the One Health Enteric Package v1.0: isolate identifiers, sample/isolate collection, human/animal host, food sample, food facility and farm environment. The result is a metadata package with a set of core attributes that describe the different aspects of the food supply chain and accepts values from controlled vocabularies and FoodON that are essential for effective use of the genomic data to inform outbreak investigation, pathogen surveillance, source attribution and risk assessment. Advantages: Incorporating ontologies to describe genomic information promotes consistent annotation for contextual metadata, enables complex queries and supports drawing inferences through automated reasoning. Analysis of genomic data layered with the appropriate metadata strengthens tools used for source attribution and risk prediction models, providing a better understanding of the occurrence of foodborne pathogens at the human, animal, and environmental interface and transmission pathways of human pathogens through the food chain. Expanding and standardizing metadata through the use of ontologies can signif